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Institute
Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150–350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma’s final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
Accurate impact parameter determination in a heavy-ion collision is crucial for almost all further analysis. We investigate the capabilities of an artificial neural network in that respect. First results show that the neural network is capable of improving the accuracy of the impact parameter determination based on observables such as the flow angle, the average directed inplane transverse momentum and the difference between transverse and longitudinal momenta. However, further investigations are necessary to discover the full potential of the neural network approach.
Azimuthal correlations of pions are studied with the quantum molecular dynamics model. Pions are preferentially emitted perpendicular to the reaction plane. Our analysis shows that this anisotropy is dominated by pion absorption on the spectator matter in the reaction plane. Pions emitted perpendicular to the reaction plane undergo less rescattering than those emitted in the reaction plane and might therefore be more sensitive to the early hot and dense reaction phase.
The properties of pions from the hot and dense reaction stage of relativistic heavy ion collisions are investigated with the quantum molecular dynamics model. Pions originating from this reaction stage stem from resonance decay with enhanced mass. They carry high transverse momenta. The calculation shows a direct correlation between high pt pions, early freeze-out times and high freeze-out densities.
We investigate the sensivity of pionic bounce-off and squeeze-out on the density and momentum dependence of the real part of the nucleon optical potential. For the in-plane pion bounce-off we find a strong sensivity on both the density and momentum dependence whereas the out-of-plane pion squeeze-out shows a strong sensivity only towards the momentum dependence but little sensivity towards the density dependence.
Triple differential cross sections of pions in heavy ion collisions at 1 GeV/nucl. are studied with the IQMD model. After discussing general properties of resonance and pion production we focus on azimuthal correlations: At projectile- and target-rapidities we observe an anticorrelation in the in-plane transverse momentum between pions and protons. At c.m.-rapidity, however, we find that high pt pions are being preferentially emitted perpendicular to the event-plane. We investigate the causes of those correlations and their sensitivity on the density and momentum dependence of the real and imaginary part of the nucleon and pion optical potential.
Abstract: An accurate impact parameter determination in a heavy ion collision is crucial for almost all further analysis. The capabilities of an artificial neural network are investigated to that respect. A novel input generation for the network is proposed, namely the transverse and longitudinal momentum distribution of all outgoing (or actually detectable) particles. The neural network approach yields an improvement in performance of a factor of two as compared to classical techniques. To achieve this improvement simple network architectures and a 5 × 5 input grid in (pt, pz) space are suffcient.
The microscopic phasespace approach URQMD is used to investigate the stopping power and particle production in heavy systems at SPS and RHIC energies. We find no gap in the baryon rapidity distribution even at RHIC. For CERN energies URQMD shows a pile up of baryons and a supression of multi-nucleon clusters at midrapidity.
Basic problems of the semiclassical microscopic modelling of strongly interacting systems are discussed within the framework of Quantum Molecular Dynamics (QMD). This model allows to study the influence of several types of nucleonic interactions on a large variety of observables and phenomena occur- ring in heavy ion collisions at relativistic energies. It is shown that the same predictions can be obtained with several numerically completely di erent and independently written programs as far as the same model parameters are employed and the same basic approximations are made. Many observ- ables are robust against variations of the details of the model assumptions used. Some of the physical results, however, depend also on rather technical parameters like the preparation of the initial configuration in phase space. This crucial problem is connected with the description of the ground state of single nuclei, which di ers among the various approaches. An outlook to an improved molecular dynamics scheme for heavy ion collisions is given.